In some cases, it can be hard to accurately provide appropriate insurance related information to a potential insurance customer. For example, a small business owner might be unsure of what types of insurance are appropriate and/or the amounts of coverage or deductibles are typical for similarly sized businesses, etc. As a result, it can be difficult for an insurance provider to suggest appropriate types of insurance policies, determine a recommended amount of insurance coverage and/or deductibles, and/or to predict likely insurance premium values for the potential customer. These difficulties can cause potential customers to miss opportunities to reduce risk and protect their enterprises. For example, an insurer might find it difficult to inform a retail florist about the appropriate types and amounts of insurance coverage similar businesses have purchased in the past. Further exacerbating these difficulties is the fact that some commercial insurance coverages are suited for use together, while others are incompatible with one another.
An insurer might manually investigate and compile information describing a business or other entity to be insured. This information may then be used recommend a set of insurance coverages based on an insurance agent's professional experience. Aggregating and reviewing this information may be a difficult task, and the lag time for generating a recommendation may make such an approach impractical, especially when there a substantial number of potential insurance customers. Moreover, the quality of the recommendation may be limited by the professional experience of the agent.
Systems and methods are desired to facilitate a customized recommendation of insurance coverages which are appropriate for a given entity. Also desired are prompt presentation of the recommendation, and/or determination of the recommendation based on significant quantities of historical data associated with other entities and insurance coverages.